# Model Reduction and Neural Networks

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/model-reduction-and-neural-networks-2/

## Facts

| Field | Value |
| --- | --- |
| Citations | 734,873 |
| Description | This cluster of papers focuses on the development and application of physics-informed neural networks for scientific computing, particularly in the context of solving partial differential equations, model reduction, fluid dynamics, dynamic mode decomposition, and nonlinear systems. The research explores the integration of deep learning techniques with traditional numerical methods to address complex problems in physics-based modeling and simulation. |
| Domain | Physical Sciences |
| Field | Physics and Astronomy |
| OpenAlex ID | https://openalex.org/T11206 |
| Works | 71,568 |

## Topic researchers

Showing 12 of 20.

- [Yoshua Bengio](https://scholariq.org/researchers/yoshua-bengio/)
- [Geoffrey E. Hinton](https://scholariq.org/researchers/geoffrey-e-hinton/)
- [Yann LeCun](https://scholariq.org/researchers/yann-lecun/)
- [Jerome H. Friedman](https://scholariq.org/researchers/jerome-h-friedman/)
- [Demis Hassabis](https://scholariq.org/researchers/demis-hassabis/)
- [Kalyanmoy Deb](https://scholariq.org/researchers/kalyanmoy-deb/)
- [David Silver](https://scholariq.org/researchers/david-silver/)
- [Koray Kavukcuoglu](https://scholariq.org/researchers/koray-kavukcuoglu/)
- [Bernhard Schölkopf](https://scholariq.org/researchers/bernhard-scholkopf/)
- [Stephen Boyd](https://scholariq.org/researchers/stephen-boyd/)
- [James E. Gunn](https://scholariq.org/researchers/james-e-gunn/)
- [Sepp Hochreiter](https://scholariq.org/researchers/sepp-hochreiter/)

---
Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.